Principal Component Analysis for Feature Reduction
What is Principal Component Analysis? Principal component analysis (PCA) Reduce the dimensionality of a data set by finding a new set of variables, smaller

2806 Neural Computation Principal Component Analysis
The following principles provide the neurobiological basis for the adaptive algorithms for principal component analysis: Some reduction. Let the data vector a feature space that is

Principal Component Analysis Based on L1-Norm Maximization
In data analysis problems, why do we need dimensionality reduction? Principal Component Analysis(PCA) PCA we can compute the variance of the feature. The